Multiscale denoising algorithm based on the a trous algorithm

Abstract

In this work we present a novel application of the multiscale denoising algorithm proposed by Sita and Ramakrishnan (2000). We used it to filter artificially contaminated images by multiplicative speckle and additive Gaussian noise, respectively. This filtering scheme is a combination of the shift invariant discrete wavelet and nonlinear filtering applied to evoked potential signals. It employs a redundant discrete wavelet (the a trous algorithm) removing the smallest wavelet coefficients in each dyadic scale guided by the correlation existing between them in different scales.